Theme network is a semantic network of document specific themes. So far Natural Language Processing (NLP) research patronized much of topic based summarizer system, unable to capture thematic semantic affinity of any text i.e. a news article containing the concepts, "gun," "convenience store," "demand money" and "make getaway" might suggest the topics "robbery" and "crime". In this paper the development of an opinion summarization system that works on Bengali News corpus has been described. The system identifies the sentiment information in each document, aggregates them and represents the summary information in text. The present system follows a topic-sentiment model for sentiment identification and aggregation. Topic-sentiment model is designed as discourse level theme identification and the topic-sentiment aggregation is achieved by theme clustering (k-means) and Document level Theme Relational Graph representation. The Doc...